The Influence of Shopping Website Design on Consumer’s Intention to Buy Online: The Case of 3D vs. 2D Online Book Stores

As increasing number of consumers take their business on-line, retailers try to gain competitive advantage through innovativedesign of their electronic storefronts. In the last few years, more and more three dimensional online stores (3D) have becomean alternative to the more traditional two dimensional ones (2D). The goal of this study is to examine the influence ofshopping website design (3D vs. 2D websites) on consumer’s intention to buy online. We draw from research in electroniccommerce, web-site design, technology acceptance and psychology, and propose a model that seeks to explain the influenceof online store front design on shopping outcomes through of such mediators as user perceptions and cognitive absorption.The proposed model offers useful insights to researchers and practitioners alike

Valuation of Personal Data in the Age of Data Ownership

In order to tackle uncertainties about data ownership and data misuse, more accessible and competitive data markets are proposed, especially concerning the use and access rights of data generated by the Internet of Things (IoT) devices. Legal proposals suggest that companies and individuals become owners of their self-generated data, enabling new ways of data monetization. Still, individuals are often uncertain about the value and price of their own generated data. This research builds on construal level theory to propose influencing factors fostering an understanding of intraindividual data value. The results of a pilot study survey (n = 104), conducted during the ICIS 2022, show that data proximity and data sensitivity factors significantly influence intraindividual data value. Our research extends the knowledge on data value from individual perspectives and builds the foundation for future work on data valuation and pricing in intraindividual data trading

The Influence of Business Intelligence Components on the Quality of Decision Making

Decision makers require the right information at the right time, in the right place and in the right format so that they can make good decisions. Although business intelligence (BI) has the potential to improve decision making, there is little empirical evidence of how well this has been achieved. The purpose of this dissertation is to examine the quality of decisions made using BI. The research question it addresses is what are the key antecedents of decision quality for users of business intelligence systems? The theoretical support for the model is developed based on the literature review that draws on decision support systems (DSS), group decision support systems (GDSS), and BI. Grounded on this literature review, the antecedents of decision quality are operationalized in this dissertation through independent variables such as the problem space complexity, the level of BI usage, the BI user experience, and information quality. The dependent variable is operationalized as decision quality and it captures the self-satisfaction with a decision made by users in a BI environment. The research model was tested using a survey of BI users whose names were provided by a marketing company. This research suggests that BI user experience is a more complex construct than has been initially thought